Instrument for measuring potentials on two dimensional electric field plots Patent
Instrument for measuring potentials on two dimensional electric field plot
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Instrument for measuring potentials on two dimensional electric field plot
A number of modern and old style liquid water content (LWC) and droplet sizing instruments were mounted on a DeHavilland DHC-6 Twin Otter and operated in natural icing clouds in order to determine their comparative operating characteristics and their limitations over a broad range of conditions. The evaluation period occurred during the 1982-1983 icing season from January to March 1983. Time histories of all instrument outputs were plotted and analyzed to assess instrument repeatability and reliability. Scatter plots were also generated for comparison of instruments. The measured LWC from four instruments differed by as much as 20 percent. The measured droplet size from two instruments differed by an average of three microns. The overall effort demonstrated the need for additional data, and for some means of calibrating these instruments to known standards.
A number of modern and old style liquid water content (LWC) and droplet sizing instruments were mounted on a DeHavilland DHC-6 Twin Otter and operated in natural icing clouds in order to determine their comparative operating characteristics and their limitations over a broad range of conditions. The evaluation period occurred during the 1982-1983 icing season from January to March 1983. Time histories of all instrument outputs were plotted and analyzed to assess instrument repeatability and reliability. Scatter plots were also generated for comparison of instruments. The measured LWC from four instruments differed by as much as 20 percent. The measured droplet size from two instruments differed by an average of three microns. The overall effort demonstrated the need for additional data, and for some means of calibrating these instruments to known standards.
Analog computer using deconvolution to improve resolution of analytical instruments
The Baltimore Ecosystem Study (BES) established a network of long-term permanent biogeochemical study plots in 1998. These plots provide long-term data on vegetation, soil and hydrologic processes in the key ecosystem types within the urban ecosystem. The network of study plots includes forest plots (upland and riparian), chosen to represent the range of forest conditions in the area and grass plots (to represent home lawns). Plots are instrumented with lysimeters (drainage and tension) to sample soil solution chemistry, time domain reflectometry probes to measure soil moisture, dataloggers to measure and record soil temperature, and trace gas flux chambers to measure the flux of carbon dioxide, nitrous oxide and methane from soil to the atmosphere. Measurements of in situ nitrogen mineralization, nitrification and denitrification were made at approximately monthly intervals from Fall 1998 - Fall 2000. Detailed vegetation characterization (all layers) was done in summer 1998 and 2015. Data from these plots has been published in Groffman et al. (2006, 2009), Groffman and Pouyat (2009), Savva et al. (2010), Costa and Groffman (2013), Duncan et al. (2013), Waters et al. (2014), Ni and Groffman (2018), Templeton et al. (2019). Literature Cited Costa, K.H. and P.M. Groffman. 2013. Factors regulating net methane flux in urban forests and grasslands. Soil Science Society of America Journal 77:850 - 855. Duncan, J. M., L. E. Band, and P. M. Groffman. 2013. Towards closing the watershed nitrogen budget: Spatial and temporal scaling of denitrification. Journal of Geophysical Research Biogeosciences 118:1-5; DOI: 10.1002/jgrg.20090 Groffman PM, Pouyat RV, Cadenasso ML, Zipperer WC, Szlavecz K, Yesilonis IC,. Band LE and Brush GS. 2006. Land use context and natural soil controls on plant community composition and soil nitrogen and carbon dynamics in urban and rural forests. Forest Ecology and Management 236:177-192. Groffman, P.M., C.O. Williams, R.V. Pouyat, L.E. Band and I.C. Yesilonis. 2009. Nitrate leaching and nitrous oxide flux in urban forests and grasslands. Journal of Environmental Quality 38:1848-1860. Groffman, P.M. and R.V. Pouyat. 2009. Methane uptake in urban forests and lawns. Environmental Science and Technology 43:5229-5235. DOI: 10.1021/es803720h. Ni, X. and P.M. Groffman. 2018. Declines in methane uptake in forest soils. Proceedings of the National Academies of Science of the United States of America 115:8587-8590. Savva, Y., K. Szlavecz, R. V. Pouyat, P. M. Groffman, and G. Heisler. 2010. Effects of land use and vegetation cover on soil temperature in an urban ecosystem. Soil Science Society of America Journal 74:469-480. Templeton, L., M.L. Cadenasso, J. Sullivan, M. Neel and P.M. Groffman. 2019. Changes in vegetation structure and composition of urban and rural forest patches in Baltimore from 1998 to 2015. Forest Ecology and Management. In press. Waters, E.R., J.L. Morse, N.D. Bettez and P.M. Groffman. 2014. Differential carbon and nitrogen controls of denitrification in riparian zones and streams along an urban to exurban gradient. Journal of Environmental Quality 43:955–963.
Three-dimensional manipulation and plotting program for digital computer and digital plotter
Low Earth Orbit (LEO) and Geosynchronous Earth Orbit (GEO) satellite plots are given. All satellites are in an 800 km circular orbit at an inclination of 98.6 deg (sun synchronous). Specifics of the instrument package are given. Additionally, the time period of the plot and the percentage of the Earth covered during the time period are listed.
Vacuum tube bridge operates in two modes, tracing and fixed potential. It reduces plotting time by fifty percent and improves measurement precision.
This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. * Todorov and Worsham are co–first authors.
The concept of the well-known Langley plot technique, used for the calibration of ground-based instruments, has been generalized for application to satellite instruments. In polar regions, near summer solstice, the solar backscattered ultraviolet (SBUV) instrument on the Nimbus 7 satellite samples the same ozone field at widely different solar zenith angles. These measurements are compared to assess the long-term drift in the instrument calibration. Although the technique provides only a relative wavelength-to-wavelength calibration, it can be combined with existing techniques to determine the drift of the instrument at any wavelength. Using this technique, we have generated a 12-year data set of ozone vertical profiles from SBUV with an estimated accuracy of +/- 5% at 1 mbar and +/- 2% at 10 mbar (95% confidence) over 12 years. Since the method is insensitive to true changes in the atmospheric ozone profile, it can also be used to compare the calibrations of similar SBUV instruments launched without temporal overlap.
Infrared microscope instrument measures and plots the infrared profile of semiconductor chips, transistors and integrated circuits. Infrared analyses yields information on electrical and physical properties, enabling manufacturing improvements in semiconductor performance and reliability. Operational performance and main sections of the instrument are given.
A spectrum of M87 obtained in the 1150-2000 A spectral range by the IUE is discussed. The visual and UV energy distribution of the nucleus of M87 reveals an essentially continuous curve from 1300 to 10,500 A, and a turnup in flux below 2200 A. It is shown that this turnup is not a consequence of scattered light in the instrument, while a plot of the deconvolved M87 UV profile and the visual profile shows that the radiation in the 1300-2200 A spectral region is distributed in the same way as the visual radiation; it is not a point source. In addition, there is evidence in the UV for an emission line of C IV; the relative strengths of C IV, H beta, and the forbidden O III lines at 4959 and 5007 A are consistent with those seen in planetary nebulae, but the forbidden O II line at 3727 A is much too strong.
Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 (LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were disparities between the number of different types of returns and intensity values when comparing the results from two LiDAR sensors, indicating that predictive models developed using such metrics are not transferable between datasets with different acquisition parameters. Each of the indices were significantly correlated with one another, with one exception (LAI proxy), in particular those indices calculated from all returns, which indicates similarities in information content for those indices. It can then be argued that LiDAR indices have reached a similar stage in development to those calculated from optical-spectral sensors, but which offer a number of advantages, such as the reduction or removal of saturation issues in areas of high biomass.
This data set provides a record of the aerial images of the SPRUCE experimental plots obtained periodically using an unmanned aerial vehicle (UAV) with attached camera from 2019-05-05- to 2022-08-25. New images of the plots will be added periodically. The initial RGB images may be used for studies of greenness and snow coverage and compared with ground-based measurements and chamber-based tree and shrub Phenocam images (e.g. Schädel et al., 2022). Also included are NDVI (Normalized Difference Vegetation Index) images showing calculated difference between visible near-infrared (NIR) light reflectance from vegetation, as well as infrared (IR) and multispectral images. Files are presented in JPEG (*.jpg) or PDF (*.pdf) format inside of 28 compressed (*.zip) files. Images were collected for the 10 plots with enclosures, the 7 unchambered plots, and the environmental monitoring instrument cluster area. Images are slightly off-plot center at 12 to 15 meters above ground level or approximately 2 meters above the top of an experimental chamber.
This dataset consists of observations of Normalized Difference Vegetation Index (NDVI) observations from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Measurements were collected via stationary sensors positioned 1.5 meter above unobstructed areas of the ground layer. Sensors were installed above undisturbed community composition plots, that are not instrumented or destructively sampled in any way, in six of the ten chambered SPRUCE experimental study plots located in the S1-Bog. Spectral data (630 and 800 nanometers) were collected at 10-minute intervals over a field of view of ~53 cm in diameter beginning May 6, 2016. Data collection ended at a different time for each sensor as batteries discharged – ranging from January 1, 2018 to April 1, 2018. The spectral sensors were manufactured by Decagon Inc., (now METER) for observation of ecosystem canopies. Sensors were deployed at the beginning of the 2016 growing season in +0, +4.5, and +9.0 C temperature treatments, with one each in an ambient and elevated carbon dioxide (CO2) plot, for a total of six sensors. These data have been analyzed and reported on in McPartland et al (2018). This dataset contains one data file in comma-separate values (*.csv) format and PDF (*.pdf) file containing plot maps. Additional metadata are provided: a data dictionary and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.
A benchtop virtual instrument simulator for CERES (Clouds and the Earth's Radiant Energy System) has been built at NASA, Langley Research Center in Hampton, VA. The CERES instruments will fly on several earth orbiting platforms notably NASDA's Tropical Rainfall Measurement Mission (TRMM) and NASA's Earth Observing System (EOS) satellites. CERES measures top of the atmosphere radiative fluxes using microprocessor controlled scanning radiometers. The CERES Virtual Instrument Simulator consists of electronic circuitry identical to the flight unit's twin microprocessors and telemetry interface to the supporting spacecraft electronics and two personal computers (PC) connected to the I/O ports that control azimuth and elevation gimbals. Software consists of the unmodified TRW developed Flight Code and Ground Support Software which serves as the instrument monitor and NASA/TRW developed engineering models of the scanners. The CERES Instrument Simulator will serve as a testbed for testing of custom instrument commands intended to solve in-flight anomalies of the instruments which could arise during the CERES mission. One of the supporting computers supports the telemetry display which monitors the simulator microprocessors during the development and testing of custom instrument commands. The CERES engineering development software models have been modified to provide a virtual instrument running on a second supporting computer linked in real time to the instrument flight microprocessor control ports. The CERES Instrument Simulator will be used to verify memory uploads by the CERES Flight Operations TEAM at NASA. Plots of the virtual scanner models match the actual instrument scan plots. A high speed logic analyzer has been used to track the performance of the flight microprocessor. The concept of using an identical but non-flight qualified microprocessor and electronics ensemble linked to a virtual instrument with identical system software affords a relatively inexpensive simulation system capable of high fidelity.
Two instruments were used to size dry aerosols for the CCN experiments: the Naval Research Laboratory (NRL) instrument which uses an electrical mobility analyzer to separate the aerosol size fractions and a diffusion chamber to grow and count the particles and the University of Wyoming (WYO) aerosol monitoring system. Measurements from these two systems were usually found to be in agreement during the CCN Workshop. Two examples are presented to compare aerosol size distribution measurements of the two instruments: experiment 8 (monodisperse NaCl) and experiment 27 (polydisperse AgI). Differential (dN/dR) and cumulative plots are shown for both instruments for experiment 8 and experiment 27; also shown are Aitken particle measurements for comparison.
The windward surface temperature response measured during the fifth entry of the Space Shuttle Columbia is presented as solid filled color contour plots. These plots show the data from 92 instruments, at selected points in time, in a manner which makes the temperature extremes and gradients immediately obvious. Several physical phenomena, such as separated flow caused by the deflected body flap, local heating at the elevon-elevon gap, an overview of the propagation of boundary-layer transition over the Orbiter windward surface, and the thermal response of eight catalytically coated tiles, can be observed or inferred from the displayed temperatures. In addition, the maximums from each instrument have been contoured and are presented with a companion plot showing the percentage of surface area covered by each contour level. Also, the flight data are presented using the colors which correspond to the surface emittance as a function of temperature. To show the temperature transients, a computer-generated movie has been produced showing the temperature contours from 100 s to 1500 s after entry interface.